Salary
💰 $113,300 - $155,850 per year
Tech Stack
AzureCloudETLHadoopPySparkPythonSparkSQL
About the role
- Responsible for end-to-end model estimation and implementation, including data ETL, variable selection, and performance testing
- Involved in model deployment and validation
- Meet regularly with stakeholders to assess ongoing model performance and design choices
- Design, develop, and evaluate moderately complex predictive models and advanced algorithms
- Identify meaningful insights from large data and metadata sources
- Test hypotheses/models, analyze, and interpret results
- Exercise sound judgment and discretion within defined procedures and practices
- Develop and code moderately complex software programs, algorithms, and automated processes
- Use modeling and trend analysis to analyze data and provide insights
- Develop understanding of best practices and ethical AI
- Transform data into charts, tables, or format that aids effective decision making
- Build working relationships with team members and subject matter experts
- Lead small projects and initiatives
- Utilize effective written and verbal communication to document and present findings of analyses to a diverse audience of stakeholders
Requirements
- 3-5 years of experience in exploratory data analysis
- Basic understanding of business and operating environment
- Statistics
- Programming, data modeling, simulation, and advanced mathematics
- Python, SQL, and Databricks
- Model lifecycle execution
- Technical writing
- Data storytelling and technical presentation skills
- Research Skills
- Interpersonal Skills
- Working knowledge of procedures, instructions, and validation techniques
- Model Development
- Communication
- Critical Thinking
- Collaborate and Build Relationships
- Initiative with sound judgement
- Technical (Big Data Analysis, Coding, Project Management, Technical Writing, etc.)
- Sound Judgment
- Problem Solving (Responds as problems and issues are identified)
- Bachelor's Degree in Data Science, Statistics, Mathematics, Computers Science, Engineering, or degrees in similar quantitative fields
- Master's/PhD Degree in Data Science, Statistics, Mathematics, Computers Science, or Engineering (desired)
- Background in finance or economics (desired)
- FRM/CFA or related certification (desired)
- Experience estimating and implementing statistical models using real-world economic data (desired)
- Experience in asset-liability management and financial risk management (desired)
- Understanding of financial statements and types of risk faced by credit unions (desired)